Top 5 LLM Gateways for Securing Your AI Apps

Compare the top five LLM gateways for securing your AI apps, evaluated on guardrails, access governance, and compliance. Bifrost is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability.

Every prompt and response in a production AI application passes through external model providers, which exposes API keys, credentials, and regulated data at the point of each request. The OWASP Foundation ranks prompt injection and sensitive information disclosure as the two most critical risks for LLM applications, and both are best contained at a shared control point rather than inside every service. An LLM gateway is that control point: a single proxy that authenticates, routes, filters, and audits traffic to multiple model providers. This guide compares five LLM gateways for securing your AI apps, starting with Bifrost, the open-source AI gateway from Maxim AI, and evaluates each on guardrails, access governance, deployment isolation, and compliance.

What Is an LLM Gateway, and How Does It Improve Security?

An LLM gateway is a unified entry point that authenticates, routes, observes, and governs traffic to multiple LLM providers through a single API. For security, it centralizes controls that would otherwise be rebuilt in every application: input and output filtering, credential handling, access policies, and audit logging across all providers and models at once.

Building those controls inside each service is brittle. Every team rebuilds the same checks, each new model integration drifts from the standard, and audit evidence ends up scattered across services. OWASP recommends defense in depth for LLM applications, combining input validation, output filtering, and privilege restrictions, and a single control layer is the natural place to enforce all three consistently. When the controls live in one layer, a new microservice inherits the same policy the moment its traffic is routed through the gateway.

How We Evaluated These LLM Gateways

Each gateway below is assessed against the criteria that matter most for protecting a production AI application:

• Guardrails and data protection: content safety, PII detection, prompt injection blocking, and secret or credential scanning on prompts and responses
• Access governance: per-key access scoping, role-based access control, budgets, and rate limits
• Compliance and audit: immutable logging and support for SOC 2, GDPR, and HIPAA evidence
• Deployment isolation: self-hosting, VPC isolation, and air-gapped options for sensitive workloads
• Performance and reliability: request overhead, automatic failover, and throughput under load
• Provider coverage: breadth of supported model providers behind one interface

1. Bifrost: The Highest-Performance Secure LLM Gateway

Bifrost is an open-source LLM gateway written in Go and built for production AI systems that cannot trade security for speed. It adds roughly 11 microseconds of overhead per request at 5,000 requests per second in sustained benchmarks, and it exposes a single OpenAI-compatible API across 20+ model providers including OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Mistral, Cohere, and Groq.

Security is enforced at the gateway layer rather than per application. Bifrost validates inputs and outputs inline through a guardrails system built on two primitives: rules, defined with Common Expression Language, decide what to check and when; profiles decide how to check it and which provider runs the check. A single rule can chain multiple profiles, which is how the gateway delivers defense in depth on one request.

Key security and governance capabilities include:

• Guardrails and PII protection: native secrets detection catches leaked API keys and credentials, while custom regex and external providers such as AWS Bedrock Guardrails and Azure AI Content Safety handle PII redaction, content moderation, and prompt attack prevention
• Virtual keys: virtual keys replace shared provider credentials with scoped keys carrying their own budgets, rate limits, and provider access
• Access control: governance and role-based access control scope models, budgets, and tool permissions by team or role
• Audit and compliance: immutable audit logs produce trails aligned to SOC 2, GDPR, HIPAA, and ISO 27001
• Deployment isolation: in-VPC and air-gapped deployments keep guardrail and model calls off the public internet
• Reliability: automatic failover, load balancing, and semantic caching keep applications running during provider incidents
• Tool governance: the MCP gateway gives AI models controlled access to external tools, with per-key filtering over which tools each caller can reach

Teams that need a deeper view of these controls can review the guardrails capabilities and governance feature set in more detail.

Best for: Bifrost is built for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. It serves as a centralized AI gateway to route, govern, and secure all AI traffic across models and environments with ultra low latency. Bifrost unifies LLM gateway, MCP gateway, and Agents gateway capabilities into a single platform. Designed for regulated industries and strict enterprise requirements, it supports air-gapped deployments, VPC isolation, and on-prem infrastructure. It provides full control over data, access, and execution, along with robust security, policy enforcement, and governance capabilities.

2. Kong AI Gateway: Enterprise API Management Extended to AI

Kong AI Gateway brings Kong's established API management platform to LLM and agent traffic. It routes across major providers including OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure AI, Mistral, and Hugging Face, and layers governance controls on top.

Its security posture centers on data protection and policy enforcement at the proxy. Kong offers PII sanitization across a broad set of entity types and languages, integrates guardrail providers such as AWS Bedrock Guardrails and Azure AI Content Safety, and supports semantic routing and prompt compression to manage cost. The platform targets organizations with formal compliance programs spanning SOC 2, HIPAA, and GDPR.

Best for: teams already running Kong's API management platform who want to extend existing governance, observability, and compliance controls to LLM and agent traffic without adopting a separate stack.

3. Cloudflare AI Gateway: Edge Controls and Unified Billing

Cloudflare AI Gateway runs on Cloudflare's global edge network and adds application-level controls in front of multiple model providers. It consolidates billing for hundreds of models across a handful of major providers into a single bill, which simplifies multi-provider cost management.

On the security side, Cloudflare provides integrated data loss prevention that scans prompts and responses for sensitive data, plus an optional zero data retention mode for compliance-sensitive workloads. Caching, rate limiting, and dynamic routing between models round out the controls, and a free tier is available across Cloudflare plans.

Best for: teams already on Cloudflare that want unified multi-provider billing alongside edge-level controls such as data loss prevention and zero data retention.

4. LiteLLM: Broadest Provider Coverage

LiteLLM is an open-source gateway that supports 100+ model providers through a unified OpenAI-compatible interface, available as both a Python SDK and a proxy server. Its main draw is reach: few gateways match the number of providers it can address from one configuration.

Its security and governance features are configuration-driven. LiteLLM provides cost tracking and budgets per project, access controls and key management on the proxy, and connections to external observability platforms for logging and monitoring. Teams comparing it against a Go-based alternative for production load can review the considerations on the LiteLLM alternative page.

Best for: teams that need the widest possible provider coverage and are comfortable managing YAML configuration and wiring up third-party observability integrations themselves.

5. OpenRouter: Fast Access to a Large Model Catalog

OpenRouter is a hosted gateway that exposes hundreds of models from many providers through one OpenAI-compatible API, with credit-based unified billing and pay-as-you-go pricing. It handles routing and fallbacks across models, which makes it convenient for quickly accessing a wide catalog without managing separate provider accounts.

Its governance and security surface is lighter than the enterprise-focused options above. OpenRouter centralizes credentials and billing, but teams with strict requirements for inline guardrails, PII redaction, audit trails, and self-hosted or air-gapped deployment will typically need to add those controls elsewhere.

Best for: developers who want fast access to a large model catalog through a single API and credit-based billing, with lighter governance and compliance requirements.

LLM Gateway Security Comparison

The table below summarizes how each LLM gateway compares across the security dimensions above, from inline guardrails to deployment isolation.

How to Choose a Secure LLM Gateway

The right LLM gateway depends on where your security requirements are strictest. Match the decision to your threat model rather than to feature counts:

• If guardrails and data protection are the priority: choose a gateway that validates inputs and outputs inline across every provider, with secret detection and PII redaction enforced in one layer.
• If compliance evidence is the priority: require immutable audit logs and explicit support for the frameworks your auditors expect, such as SOC 2, HIPAA, or GDPR.
• If data residency is the priority: require self-hosted, VPC-isolated, or air-gapped deployment so prompts and guardrail checks never leave your network.
• If performance under load is the priority: measure request overhead at your real throughput, since a gateway sits on the hot path of every call.

For a structured way to score vendors against these dimensions, the LLM Gateway Buyer's Guide provides a capability checklist you can apply to any shortlist. Bifrost is the strongest fit when an application needs all four priorities at once: gateway-layer guardrails, compliance-grade audit, deployment isolation, and low overhead in a single open-source platform.

Frequently Asked Questions

What is the most secure LLM gateway?

The most secure LLM gateway enforces guardrails, access governance, audit logging, and deployment isolation in one layer rather than depending on application-side controls. Bifrost meets all four with inline guardrails, virtual keys and RBAC, immutable audit logs, and air-gapped or VPC deployment.

How does an LLM gateway prevent prompt injection?

An LLM gateway inspects every prompt and response against configured policies before a request reaches the model or returns to a user. Pattern-based and provider-backed guardrails flag or block injection attempts, and chaining multiple checks on a single request provides the defense in depth that OWASP recommends.

Can an LLM gateway help with SOC 2 or HIPAA compliance?

Yes. A gateway centralizes the audit evidence and access controls that compliance frameworks require. Bifrost produces immutable audit logs aligned to SOC 2, GDPR, HIPAA, and ISO 27001, and supports in-VPC and air-gapped deployment for regulated data.

Do LLM gateways add latency?

A well-engineered gateway adds minimal routing overhead, though guardrail checks add processing time proportional to the validation involved. Bifrost adds roughly 11 microseconds of routing overhead per request at 5,000 requests per second, with guardrail evaluation layered on top only where rules apply.

Securing Your AI Apps with Bifrost

Choosing among LLM gateways for securing your AI apps comes down to whether one platform can enforce guardrails, governance, compliance, and isolation without slowing requests down. Bifrost combines inline guardrails, virtual key governance, compliance-grade audit logging, and air-gapped deployment in an open-source gateway with microsecond-level overhead. To see how Bifrost can secure your AI infrastructure, book a demo with the Bifrost team or explore Bifrost Enterprise.